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The architecture of antagonistic networks

Nuwagaba, Savannah (2013-03)

Thesis (MSc)--Stellenbosch University, 2013.

Thesis

ENGLISH ABSTRACT: Designing a mechanistic model that can give rise to realistic architecture of ecological
networks is central to the understanding of how species assemble and function in ecosystems.
As species are constantly adjusting their diets in an antagonistic network, we
here incorporate this adaptive behaviour of diet choice into a bipartite network model,
with the effect of antagonistic interactions between species depicted by Holling’s type
II functional response. Predictions of this model fit extremely well with the observed
levels of nestedness, modularity and node-degree distributions for 61 real host-parasitoid
and plant-herbivore networks. We further examined two specific scenarios of our model
(species with identical [neutral] demographic parameters and interactions with identical
[neutral] benefit in the network) and found that the demography-neutral scenario overestimated
observed modularity, whilst the benefit-neutral scenario over-estimate observed
nestedness. Relationships between nestedness, modularity and connectance were found
strong. Moreover, in contrast to the common belief of the high modularity in antagonistic
networks, most real networks (> 80%) are significantly nested, whilst nearly 40% of the
real networks are surprisingly less compartmentalized than random networks generated
from null models. Regardless of the controversy on whether antagonistic networks are
nested or compartmentalized, the proposed model captured the essence of the dynamic
nature of structural emergence in antagonistic networks. Due to its predictive power, this
model was further used to investigate robustness in antagonistic networks. Predictions
showed that the robustness of a network is determined by many factors, such as connectance,
resource degree distribution, resource-consumer ratio, diversity, nestedness and
compartmentalisation. Surprisingly, the manner of network response to species loss was
independent of the sequence followed while removing species from a network. Variations
were only noticed in the intensity of the effect resulting from the removals. In addition,
we also showed that species extinction procedures which ignore the interaction switch
underestimate the effect of any loss of species in these networks. We must therefore value
our knowledge of possible adaptive processes in the ecosystem as they may be important
for resolving the diversity-stability debate.